Enhancing Compression While Transcoding JPEG Images

ABSTRACT

Further compression of data allowing economical storage of data for extended periods of time in high-speed access memory is performed in reduced time by performing further compression during transcoding in the transform domain and without restoring image data to its original image data form. The reduction in processing time is achieved by exploiting the large number of zero-valued quantization transform coefficients and not changing quantized transform coefficients at zig-zag scan positions where non-zero coefficients are rare during range reduction of the entropy decoded quantized transformed data. The range can be restored by computation or estimation of an altered quantization table which is stored with the further compressed quantization values. Further advantages accrue from use of JPEG packed format for the data during transcoding.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation application of U.S. patentapplication Ser. No. 10/263,653 filed Oct. 4, 2002, and the completecontents thereof is herein incorporated by reference. This applicationis related to U.S. patent applications Ser. No. 09/760,383, entitled“Enhanced Compression of Documents”, filed Jan. 16, 2001, now U.S. Pat.No. 6,606,418 B2, Ser. No. 09/736,444, entitled “JPEG Packed BlockStructure” filed Dec. 15, 2000, Ser. No. 09/896,110, entitled “JPEGPacked Block Structure for enhanced Image Processing”, filed Jul. 2,2001, and Ser. No. 10/183,386, filed Jun. 28, 2002, entitled “AdaptiveGeneration of Q-Table2 for Enhanced Image Quality”, all of which areassigned to the assignee of the present invention and hereby fullyincorporated by reference.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to compression of image datawhile applying corrections to enhance image quality and, moreparticularly, to the decoding and re-encoding of documents foradditional and more extreme data compression to allow economicallyacceptable long-term storage in rapid access memory and performing suchdecoding and re-encoding in reduced processing time.

2. Description of the Prior Art

Pictorial and graphics images contain extremely large amounts of dataand, if digitized to allow transmission or processing by digital dataprocessors, often requires many millions of bytes to representrespective pixels of the pictorial or graphics images with goodfidelity. The purpose of image compression is to represent images withless data in order to save storage costs or transmission time and costs.The most effective compression is achieved by approximating the originalimage, rather than reproducing it exactly. The JPEG (Joint PhotographicExperts Group) standard, discussed in detail in “JPEG Still Image DataCompression Standard” by Pennebaker and Mitchell, published by VanNostrand Reinhold, 1993, which is hereby fully incorporated byreference, allows the interchange of images between diverse applicationsand opens up the capability to provide digital continuous-tone colorimages in multi-media applications.

JPEG is primarily concerned with images that have two spatialdimensions, contain gray scale or color information, and possess notemporal dependence, as distinguished from the MPEG (Moving PictureExperts Group) standard. JPEG compression can reduce the storagerequirements by more than an order of magnitude and improve systemresponse time in the process. A primary goal of the JPEG standard is toprovide the maximum image fidelity for a given volume of data and/oravailable transmission or processing time and any arbitrary degree ofdata compression is accommodated. It is often the case that datacompression by a factor of twenty or more (and reduction of transmissiontime and storage size by a comparable factor) will not produce artifactsor image degradation which are noticeable to the average viewer.

Of course, other data compression techniques are possible and mayproduce greater degrees of image compression for certain classes ofimages or graphics having certain known characteristics. The JPEGstandard has been fully generalized to perform substantially equallyregardless of image content and to accommodate a wide variety of datacompression demands. Therefore, encoders and decoders employing the JPEGstandard in one or more of several versions have come into relativelywidespread use and allow wide access to images for a wide variety ofpurposes. Standardization has also allowed reduction of costs,particularly of decoders, to permit high quality image access to bewidely available. Therefore, utilization of the JPEG standard isgenerally preferable to other data compression techniques even thoughsome marginal increase of efficiency might be obtained thereby,especially for particular and well-defined classes of images.

Even though such large reductions in data volume are possible,particularly using techniques in accordance with the JPEG standard, someapplications require severe trade-offs between image quality and costsof data storage or transmission time. For example, there may be a needto store an image for a period of time which is a significant fractionof the useful lifetime of the storage medium or device as well asrequiring a significant amount of its storage capacity. Therefore, thecost of storing an image for a given period of time can be considered asa fraction of the cost of the storage medium or device and supportingdata processor installation, notwithstanding the fact that the imagedata could potentially be overwritten an arbitrarily large number oftimes. The cost of such storage is, of course, multiplied by the numberof images which must be stored.

Another way to consider the storage cost versus image quality trade-offis to determine the maximum cost in storage that is acceptable and thendetermine, for a given amount of quality, how long the desired number ofimages can be saved in the available storage. This is a function of thecompressed size of the images which generally relates directly to thecomplexity of the images and inversely with the desired reconstructedimage quality.

An example of such a demanding application is the storage of legaldocuments which must be stored for an extended period of time, if notarchivally, especially negotiable instruments such as personal checkswhich are generated in large numbers amounting to tens of millionsdaily. While the initial clearing of personal checks and transfer offunds is currently performed using automated equipment and isfacilitated by the use of machine readable indicia printed on the check,errors remain possible and it may be necessary to document a particulartransaction for correction of an error long after the transaction ofwhich the check formed a part.

Personal checks, in particular, present some image data compressioncomplexities. For example, to guard against fraudulent transactions, abackground pattern of greater or lesser complexity and having a range ofimage values is invariably provided. Some information will be printed ina highly contrasting ink, possibly of multiple colors, while othersecurity information will be included at relatively low contrast.Decorations including a wide range of image values may be included.Additionally, hand-written or printed indicia (e.g. check amounts andsignature) will be provided with image values which are not readilypredictable.

Even much simpler documents may include a variety of image values suchas color and shadings in letterhead, high contrast print, a watermark onthe paper and a plurality of signatures. This range of image values thatmay be included in a document may limit the degree to which image datamay be compressed when accurate image reconstruction is necessary.Therefore that cost of storage in such a form from which imagereconstruction is possible with high fidelity to the original documentis relatively large and such costs limit the period for which suchstorage is economically feasible, regardless of the desirability ofmaintaining such storage and the possibility of rapid electronic accessfor longer periods.

Since such image values must be accurately reproducible and utilizationof the JPEG standard is desirable in order to accommodate widespreadaccess and system intercompatibility, substantially the only techniquefor further reduction of data volume consistent with reproduction withgood image fidelity is to reduce the spatial frequency of sampling ofthe original image. However, sampling inevitably reduces legibility ofsmall indicia, especially at low contrast. Currently, sampling at 100dots per inch (dpi) or pixels per inch (about a reduction of one-thirdto one-sixth from the 300 dpi or 600 dpi resolutions of printerscurrently in common use) is considered to be the limit for adequatelegibility of low-contrast indicia on personal checks. The AmericanNational Standards Institute (ANSI) standards committee for imageinterchange recommends 100 dpi as a minimum resolution. Most checkapplications use either 100 dpi or 120 dpi grayscale images when theyare compressed with more than one bit per pixel.

As a practical matter, the needed quality of the image data also changesover time in such an application. For example, within a few months ofthe date of the document or its processing, questions of authenticityoften arise, requiring image quality sufficient to, for example,authenticate a signature, while at a much later date, it may only benecessary for the image quality to be sufficient to confirm basicinformation about the content of the document. Therefore, the image datamay be additionally compressed for longer term storage when reducedimage quality becomes more tolerable, particularly in comparison withthe costs of storage. At the present time, personal check images areimmediately stored for business use on DASD for about 90 days andtransferred to tape for archival purposes and saved, for legal reasons,for seven years. Thus, data is available for only a few months in“on-line”, rapid-access storage and some significant processing time isrequired for transfer to tape.

In this regard, the number of personal checks and other documentsproduced on a daily basis, itself, presents several problems. Theprocessing required for encoding and/or decoding an image is substantialand may require significant amounts of time even when performed atextremely high speed on general purpose or special purpose processors.Even when an encoding or decoding process may be performed in a fractionof a second (e.g. 1/10 second or less), the sheer number of documentsmay occupy the entire processing capacity of a large number ofprocessors on a continual basis. To reduce storage costs as reducedimage quality becomes increasingly tolerable over time, as discussedabove, even more processing has been required. That is, to increasecompression of an image from data which has already been compressed, asdiscussed in the above-incorporated patent application Ser. No.09/760,383, it is necessary to first decode the image from compresseddata and then encode the image again using different quantization tablesin order to further reduce the volume of data. This processing timerepresents a substantial cost which effectively increases the cost ofstorage over the cost of the reduced amount of storage medium occupied.Conversely, if the cost of processing for further data reduction can bereduced, the data may be stored for a longer period of time and/or inmemory having shorter access or retrieval time at an economicallyacceptable cost.

SUMMARY OF THE INVENTION

It is therefore an object of the present invention to provide an imagedata processing method and apparatus capable of increasing the degree ofcompression of compressed data and reducing the volume of image data inreduced processing time.

In order to accomplish these and other objects of the invention, amethod and apparatus is provided for transcoding compressed data forfurther compression including steps (or arrangements for performingsteps) of entropy decoding compressed data to form quantized transformcoefficient values, reducing a range of the quantized transformcoefficient values to form quantized transform coefficient values ofreduced range, altering at least one value in a quantization table toform an altered quantization table, entropy encoding said quantizedtransform coefficient values of reduced range to form further compresseddata, and transmitting or storing the further compressed data with thealtered quantization table.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, aspects and advantages will be betterunderstood from the following detailed description of a preferredembodiment of the invention with reference to the drawings, in which:

FIG. 1 is a flow chart or high-level block diagram illustrating anexemplary technique of increasing the degree of compression ofcompressed image data, and

FIG. 2 is a flow chart or high-level block diagram illustratingprocessing of compressed image data to increase the degree ofcompression in reduced processing time in accordance with the invention.

DETAILED DESCRIPTION OF A PREFERRED EMBODIMENT OF THE INVENTION

Referring now to the drawings, and more particularly to FIG. 1, there isshown a flow chart or high-level block diagram illustrating an exemplarytechnique of increasing the degree of compression of compressed imagedata. This Figure is substantially the same as FIG. 7 of theabove-incorporated U.S. patent application Ser. No. 09/760,383, which isprincipally directed to an apparatus and method for producing increasedcompression of document image data to a much reduced volume whilemaintaining legibility and document image quality and compatibility withstandard decoding processes and without post-processing. This functionis accomplished by reducing the dynamic range of the image data,encoding the data of reduced dynamic range using a first quantizationtable and storing or transmitting the encoded image data with adifferent quantization table which restores the dynamic range of theoriginal image data during otherwise conventional decoding. Inparticular, this Figure depicts application of that technique to imagedata that has already been compressed by encoding in accordance with theJPEG standard. Accordingly, no portion of FIG. 1 is admitted to be priorart in regard to the present invention but is labelled “Related Art”since it is provided to facilitate an understanding of the presentinvention and its meritorious effects as illustrated in FIG. 2 anddiscussed below even though the distinguishing features of the presentinvention are not reflected therein.

More specifically, the image values present in images of documents allowa reduction in dynamic range of the image values which can be laterrestored while preserving detail and legibility. Such a reduction indynamic range, while theoretically causing some loss of information andimage fidelity, allows further compression of the image data beyond thatcurrently employed for short term, high-speed access storage and areduction of data volume by a factor usually in the range of two to fiveor more while maintaining the image quality at a level which is legible.Legibility of low contrast features may even be enhanced, as discussedin the above-incorporated application.

Such a reduction in data volume would reduce storage costs by a similarfactor if the costs of processing are not considered. However, asalluded to above, it has been found desirable to store large numbers ofdocuments such as personal checks. However, the cost of processing largenumbers of documents already stored in compressed form in databases inorder to reduce future storage costs or to provide higher speedaccessibility would be quite substantial.

This cost can be more readily understood from consideration of FIG. 1which depicts the process for further reducing data volume fromdigitally stored data for a single document. First, the image isretrieved 710 and, if compressed 720 with any compression techniqueincluding lossless coding rather than stored as raw image data, it isdecompressed/decoded 730 by an appropriate decoder to restore theoriginal image data. Optional histogram and pre-processing discussed inthe above incorporated application are not illustrated in FIG. 1 but maybe included if desired. In block 740, the range of the image is reduced,If, as determined at 750, the reduced range image data is to becompressed, (possibly with a different compression technique), it isencoded 760. Then the reduced range image (with or without compression)is stored with range expansion information 770. For the JPEG DCT-basedcompression, this range expansion information can be in the form ofsubstituted, scaled Q table2. For other applications, it may be in theform of a JPEG-LS output remapping table.

As will be readily understood by those skilled in the art, the decodeimage process 730 includes entropy decoding, dequantizing and an inversediscrete cosine transform (IDCT) process. Entropy decoding is a processwhich can be carried out relatively rapidly. (Entropy coding exploitsthe fact that more common values justify fewer bits and less commonvalues, representing relatively more information, justify use ofrelatively more bits.) On the other hand, dequantization and the IDCTprocesses are considerably more computationally intensive. The processfor reducing the range of the image 740 can be carried out using alook-up table requiring two memory accesses and one storage operationfor each image data sample. The process of encoding an image 760requires a forward discrete cosine transform (DCT) operation,quantization and entropy encoding, which are computationally intensive.

It will also be readily understood and appreciated by those skilled inthe art that the above process of FIG. 1 reconstructs the image datafully and sufficiently for display or other rendering (e.g. printing)while processes 740-770 are identical to processes which would beperformed on raw image data in accordance with the above-incorporatedapplication to accomplish an increased degree of compression beyondstandard JPEG processing while maintaining detail and legibility offeatures of the document image. Therefore, the data could be describedas being converted from the transform domain to the image domain(sometimes referred to as the real and/or pixel domain) and back to thetransform domain. Thus, processes are involved which are substantiallyinverse processes of each other, either or both of which may becomputationally intensive and require significant processing time whenaggregated over a large plurality of documents.

The present invention provides the same result while the data remains inthe transform domain and thus avoids performance of several pairs ofsubstantially inverse and complementary processes while engendering someadditional compression of data as will be described below. The processis well-described as transcoding since the data is not returned to itsoriginal form. The basic process of the invention will now be explainedin accordance with the flow chart of FIG. 2 which can also be understoodas a high-level block diagram of apparatus for carrying out theillustrated functions as in a programmed general purpose computer whichwill be configured by the program into arrangements for performing theillustrated functions or similarly configured special purpose logicprocessing circuits, as will be evident to those skilled in the art.

It is assumed for purposes of the following discussion that the imagedata will already be encoded in some compressed form such as code incompliance with the JPEG standard. It should be understood that theinvention is completely applicable to any other compression encodingscheme and that the above assumption merely avoids the case where theoriginal data is not in a compressed form (e.g. raw image data) forwhich suitable and preferred methodologies and apparatus are provided inthe above-incorporated application.

As an overview of the process and apparatus in accordance with theinvention, once the compressed image data is retrieved (210), thecompressed data is entropy decoded 220 to restore the data to the formof quantized coefficients. The dynamic range of the quantizedcoefficients can then be directly reduced as illustrated at 240 andentropy encoding 260 performed, preferably with simplified processeswhich will be discussed in detail below. The further compression is thencompleted by storing (or otherwise transmitting) the resulting entropyencoded data with expansion information as illustrated at 270. Theexpansion information may be complementary to the range reduction or maybe chosen to provide some image enhancement.

By avoidance of pairs of inverse, complementary operations, as alludedto above, the entropy decoding process 230 can generally be performed inless than one-quarter of the processing time required for the completeimage decoding process 730 of FIG. 1. Similarly, the entropy encodingprocess can be generally completed in less than one-quarter of the timerequired for the complete image encoding process regardless of thecompression technique or standard employed. In general, the process ofreducing the range of the quantized coefficients can be performed muchmore rapidly than the reduction of the dynamic range of image data,particularly by preferred techniques which will be discussed below.Therefore, the gain in processing speed provided by the invention is atleast a factor of four and often can be much greater, even allowing forthe use of special-purpose processors for DCT and IDCT and quantizationand dequantization processing.

The entropy decoding and encoding processes are well-understood and neednot be discussed further except to observe that for entropy encoding,statistical analyses can often be omitted or replaced by relativelysimple manipulations of the entropy coding of the original compresseddata or alternatives to entropy encoding accommodated by the JPEGstandard. The process of reducing range of the quantized coefficients240 can be accomplished using a look-up table (LUT) which implies twomemory accesses and a storage operation for each quantized coefficientprocessed or requiring reduction in range as does the correspondingoperation 740 of FIG. 1 for each image sample. However, the number ofsamples in the image data of FIG. 1 is always sixty-four per macroblockwhile the number of quantized coefficients (including some zero-valuedcoefficients in accordance with coding conventions) for the samemacroblock (preceding the end-of-block (EOB) marker/symbol) is oftenmuch less than sixty-four and often much less than sixteen. Further,since only the non-zero quantized coefficients can be reduced, theactual number of quantized coefficients is often even less. Moreover,some coefficients may be left unchanged when the rarity of non-zerocoefficients at a zig-zag scan position (i.e. position in thetransformed block) does not justify the extra computation and possibleedge degradation, in which case, the quantization value corresponding totheir position must also be left unchanged in the range restorationdata. Therefore, the processing time to reduce the range of thequantized coefficients is, as a practical matter, often much less thanone-quarter of the time required to reduce dynamic range of the imagesamples.

Further, if the range reduction is constant for all quantizedcoefficients which have their range reduced, only one LUT is required.Even more simple and expeditious arrangements often provide goodresults. For example, it is preferred in some cases to reduce the rangeby a factor of two which removes the need for any LUT and the rangereduction can be achieved by a simple shift on the magnitude.

A special case of this simple range reduction embodiment is where thedata is maintained or presented in a packed format as disclosed in theabove-incorporated U.S. patent applications Ser. No. 09/736,444, nowU.S. Pat. No. 6,757,439, and/or Ser. No. 09/896,110 in which the rangereduction by powers of two involves subtracting the number of powers oftwo from the size in the preceding RS byte. If the size value in the RSbyte is less than the powers of two in the range reduction, thecoefficient has been reduced to zero and the number of coefficients inthe run must be extended to merge the new zero coefficient with the runsof zeros, if any, on either side of it. However, the total number ofbytes in the reduced range data in the new packed format will remain thesame or, more often, be reduced and it is impossible for a greaternumber of bits or bytes to be required in the JPEG packed format. Thus,while a slight amount of relatively simple additional processing may berequired using a JPEG packed format, the same buffers may be overwrittenwith the reduced range data. The reduced range data is then entropyre-encoded to obtain the much increased compression. It should be notedin this regard that the buffer holds uncompressed quantized coefficientsrequiring at least two non-zero bytes per coefficient while the Huffmancode may only require a few bits.

In general, for maximum data compression, the JPEG arithmetic codingoption can be used to automatically provide entropy re-encoded dataclose to the entropy limit; thus improving compression while avoidingany image degradation and avoiding some processing time for collectionof statistics for custom Huffman entropy encoding. The data can then beconverted to baseline JPEG at a later time if desired.

Further in regard to the JPEG packed format, it was disclosed in theabove-incorporated applications that certain processing is facilitatedthereby. In particular, the JPEG packed format allows simplifiedgeneration of custom Huffman tables for the reduced range encoder.Custom Huffman tables can be saved with the arithmetically coded imagefor later transcoding back to baseline JPEG compression. These DefineHuffman Table (DHT) markers could be stored separately from the JPEGimage encoded data in a JPEG-abbreviated-for-table-specification dataformat so that those extra bytes are not transmitted if the arithmeticcoded version is sufficient. (Note that the DHT marker will not beneeded if a Huffman version will not be desired. The DHT marker is usedif a transcoding to Huffman is needed because the decoder of thereceiver does not know how to decode the more compressed arithmeticcoding version.) Alternatively, the unused custom Huffman table(s) canbe saved in a JPEG Application Marker (APPn marker) as detailed in theabove incorporated Pennebaker et al. publication. The fields of such amarker can be registered to allow interpretation of the data. Suchmarkers may be embedded with the image data or kept separately.

If care is taken in the range reduction process, an approximate customHuffman table can be estimated from the tables prior to range reduction.For example, the shift in the probability distribution can be estimatedfrom the amount of range reduction applied. If the Huffman table in thedecoder is not the exemplary Huffman table given in the JPEG standard,it may be assumed to be a custom table, particularly if the RS symbolvalues are not in numeric order. If some distribution is assumed thatcorresponds to the number of symbols per code word lengths, then the newdistribution can be computed given the amount of dynamic rangereduction. If the code for a given R/S symbol is N bits, then the sum ofall the relative fractions within the group add up to ½^(N). Therelative frequency may be equally divided between all of the 2^(N)levels within the category. Alternatively, it can be adjusted so thatsmaller levels are more likely. As long as the total relative frequencymatches the relative frequency of the original categories, the sameHuffman code lengths would be assigned to the unchanged data. A dynamicrange reduction then clusters the levels together. For levels that donot reduce to zero, these clusters can then be combined to collect therelative frequency of the categories. A conservative estimate wouldignore the effect of the runs becoming longer. Note that the runs cannotbecome shorter since no new non-zero coefficients can be created. Anestimate of the effect of the End-of Block (EOB) occurring earlier canbe empirically determined by observing how typical images change theirstatistics for the desired range reduction. Care must be taken that allpossible runs of zeros combined with sizes up to the maximum possibleare allowed since the previous custom table may have had gaps for unusedsymbols and, unless the actual histogram is collected, such gaps are notallowed. As long as this condition is satisfied, this expedient allowsimmediate transcoding from one custom Huffman table to another customHuffman table without having to collect the new histogram; assisting inpreservation of the gain in processing time reduction which is otherwiseachieved by the invention.

It was alluded to above that some of the quantized coefficients need notbe changed or modification suppressed when the extra compression doesnot justify the computation and possible edge degradation. The decisionabout whether quantized transformation coefficients in particularzig-zag scan order positions should or should not be modified could bemade on the basis of an optional histogram of the number of non-zerotransform coefficients at each zig-zag scan position or, for example,estimated from a custom Huffman table in the original data. The largestgain in compression will be achieved for those zig-zag scan positionswith frequently occurring non-zero quantized transform coefficients. Forpositions in which non-zero quantized transform coefficients occurrarely, the gain in compression will not justify the computation time orthe degradation in image quality, even if very slight. Thus thestatistics of the number of non-zero quantized transform coefficients,however derived or estimated, can provide an estimation of thecompression gain and storage savings and thus assist in identifyingzig-zag scan positions in which quantized coefficients should not bechanged.

For example, on the reverse side of checks, endorsements will not alwaysbe of high contrast while the safety pattern is likely to have verydifferent statistics in much higher/larger numbers. If the rationale ofnot modifying quantized transform coefficients at zig-zag scan positionswith relatively infrequently occurring non-zero quantized coefficientsis applied in such a case, it is likely that image values of theendorsement will not be modified as much and may result in preservingthe legibility and detail of the endorsements. One significant advantageto doing the range reduction in the transform domain rather than thereal or pixel domain is this ability to treat transform coefficients atdifferent positions in the zig-zag scan order in a different manner andthus preserve image feature which may be of increased significance (asmay be indicated by relative frequency of occurrence) while achievingextreme data compression.

If a custom Huffman table has been used (or is included in casetranscoding of the arithmetic coding to baseline Huffman tables were tobe needed) the number of bits assigned to the End-of-Block (EOB) codecan be included in the function used to estimate the zig-zag scanposition at which to stop modifying the coefficients. In the ACcoefficient Huffman code tables listed in annex K of the JPEG technicalspecification (included in the text incorporated by reference above) theEOB has a four bit code length in the luminance table as compared to atwo bit code length in the chrominance table. Combined with the lengthsof the other run/size combinations, an estimate of when in the zig-zagscan order to stop modifying the coefficients can be obtained, as wellas an estimate of the bit savings from the modifications. The longercode length for the EOB in the luminance AC coefficient table indicatesthat quantized transform coefficients should be modified at more zig-zagscan positions.

In this regard, care must also be taken to avoid allowing changedquantization table values from exceeding 255 for eight-bit precision inthe original samples (or other maximum based on the original precisionof the data). (A zero value is not allowed and thus the allowed range is1 to 255.) If the quantization values of the decoder are already at 255before alteration to compensate for range reduction, those quantizedcoefficients can be set to zero if less than the range reduction but notreduced since the quantization values are already at their maximum valueand the additional range restoration is not feasible when thequantization values are restricted to eight bits (e.g. for baselineentropy coding).

In view of the foregoing, it is seen that the invention provides asubstantial reduction in processing time for increasing compression ofdocument image data by performing the additional compression duringtranscoding the encoded signal by doing range reduction in the transformdomain after just entropy decoding that avoids the computationallyintensive dequantization, inverse transform to the real/image domain,range reduction in the real/image domain followed by a forward transformto return to the transform domain and a re-quantization before beingable to do the entropy re-encoding. Therefore, processing time forfurther compression in accordance with the invention is likely to be notmore than one-quarter of the processing time required when compressionis performed in the real or image pixel data domain.

When the quantized coefficients are scaled down, the statistics for theHuffman table are changed. A revised Huffman table can be estimated byusing the old table to estimate the relative frequencies of the symbolsand then scaling the symbols appropriately. For example, scaling downthe quantized coefficients by a factor of two will merge adjacentcoefficient frequencies. On the average, each Huffman code will need oneless bit less for this case because two frequencies will have beencombined.

This reduction in processing time and expense corresponds to a directand substantial reduction of the cost of storage of images in order toeconomically provide high speed and “on line” access to such images foran extended period of time and allows such benefits to be provided morereadily and efficiently to existing databases of such data in compressedform.

While the invention has been described in terms of a single preferredembodiment, those skilled in the art will recognize that the inventioncan be practiced with modification within the spirit and scope of theappended claims. In particular, the invention can be readily applied tocompressed data which has been compressed by any compression techniqueand other lossy, transform-based compression algorithms as well astechniques conforming to the JPEG standard.

1. A method for transcoding compressed data for further compression while said compressed data remains in the transform domain including steps of entropy decoding said compressed data to form quantized transform coefficient values, reducing a dynamic range of said quantized transform coefficient values to form quantized transform coefficient values of reduced dynamic range, wherein some or all scan positions are reduced in dynamic range in different manners in addition to scaling, altering at least one value in a quantization table to form an altered quantization table having values based on range reduction of quantized coefficient values of reduced range at respective zig-zag scan order locations, entropy encoding said quantized transform coefficient values of reduced range to form further compressed data, and transmitting or storing said further compressed data with said altered quantization table.
 2. The method as recited in claim 1, wherein said step of reducing a dynamic range reduces said range by a factor of two.
 3. The method as recited in claim 1, wherein altered quantization values are in the range of 1 to 255 for eight bit precision in original data samples.
 4. The method as recited in claim 2, wherein altered quantization values are in the range of 1 to 255 for eight bit precision in original data samples.
 5. The method as recited in claim 1, including the further step of altering a Huffman table based on the alteration of the quantized coefficients without collecting new statistics for an image.
 6. The method as recited in claim 5, wherein frequency of occurrence is estimated from original Huffman table data.
 7. The method as recited in claim 5, wherein frequency of occurrence is determined from a histogram of said quantized transform coefficient values.
 8. The method of claim 1, wherein said entropy encoding step includes arithmetic coding.
 9. The method of claim 1, wherein said quantized transform coefficient values are in packed format.
 10. The method as recited in claim 1, wherein said step of altering said at least one value in said quantization table is complementary to said step of reducing a dynamic range for said at least one value.
 11. The method as recited in claim 2, including the further step of altering a Huffman table based on the alteration of the quantized coefficients without collecting new statistics for an image.
 12. The method as recited in claim 11, wherein frequency of occurrence is estimated from original Huffman table data.
 13. The method as recited in claim 11, wherein frequency of occurrence is determined from a histogram of said quantized transform coefficient values.
 14. The method of claim 2, wherein said entropy encoding step includes arithmetic coding.
 15. The method of claim 2, wherein said transform coefficient values are in packed format. 16-17. (canceled)
 18. Apparatus for transcoding compressed data for further compression while said compressed data remains in the transform domain comprising means for entropy decoding said compressed data to form quantized transform coefficient values, means for reducing a dynamic range of said quantized transform coefficient values to form quantized transform coefficient values of reduced dynamic range, wherein some or all scan positions are reduced in dynamic range in different manners in addition to scaling, means for altering at least one value in a quantization table to form an altered quantization table having values based on range reduction of quantized coefficient values of reduced range at respective zig-zag scan order locations, means for entropy encoding said quantized transform coefficient values of reduced range to form further compressed data, and means for transmitting or storing said further compressed data with said altered quantization table. 